This capstone project course will give you a taste of what data scientists go through in real life when working with data.
You will learn about location data and different location data providers, such as Foursquare. You will learn how to make RESTful API calls to the Foursquare API to retrieve data about venues in different neighborhoods around the world. You will also learn how to be creative in situations where data are not readily available by scraping web data and parsing HTML code. You will utilize Python and its pandas library to manipulate data, which will help you help you refine your skills for exploring and analyzing data.
Finally, you will be required to use the Folium library to great maps of geospatial data and to communicate your results and findings.
If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge upon successful completion of the course.
LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

Na lição

Neighborhood Segmentation and Clustering

In this module, you will learn about k-means clustering, which is a form of unsupervised learning. Then you will use clustering and the Foursquare API to segment and cluster the neighborhoods in the city of New York. Furthermore, you will learn how to scrape website and parse HTML code using the Python package Beautifulsoup, and convert data into a pandas dataframe.